Research
On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

Trend · papers per month

36811 · Feb 202019922001200920172026
48 results for Passive LPs

JIT liquidity providers can sometimes reduce overall market liquidity by crowding out passive LPs.

problem JIT liquidity providers can reduce overall market liquidity by crowding out passive LPs.
method Game-theoretic model with asymmetrically informed agents to analyze JIT liquidity provision in blockchain-based decentralized exchanges.
result JIT LPs only provide liquidity to uninformed orders and crowd out passive LPs when order volume is not sufficiently elastic to pool depth, potentially reducing overall market liquidity.

Optimal fees protect passive LPs in AMMs under varying market conditions.

problem Adverse selection losses in AMMs are not offset by static trading fees.
method Dynamic reduced-form model with parallel AMM and CEX, large-scale simulations, real market data analysis.
result Optimal AMM fees are stable under normal conditions but high in volatile periods to protect LPs.

This paper extends liquidity returns in geometric mean markets to time-varying weights.

problem Understanding returns and no-arbitrage prices in geometric mean markets with time-varying weights.
method Extending known results for constant-weight G3Ms to the general case of G3Ms with time-varying and potentially stochastic weights.
result LP shares can replicate the payoffs of financial derivatives and various trading strategies.

Optimizes liquidity withdrawal timing for AMM LPs to balance fees and impermanent loss.

problem Balancing fees and impermanent loss in automated market makers.
method Stochastic control problem with endogenous stopping time, numerical solutions via Euler scheme and Longstaff-Schwartz method.
result Optimal exit strategy depends on volatility, fees, and market dynamics.

Detects potential depegs in Curve's StableSwap pools to protect LPs.

problem Detecting and alerting LPs to potential depegs in Curve's StableSwap pools.
method Constructed metrics based on price and trading data, fine-tuned BOCD algorithm.
result Model detects USDC depeg 5 hours before price dip, with few false alarms.

Sharp Lp affine isoperimetric inequalities are established for the entire class of Lp projection bodies and the entire class of Lp centroid bodies. These new inequalities strengthen the Lp Petty projection and the Lp Busemann--Petty centroid inequality.

2008-09-11abs ↗pdf ↗

FLAIR measures LP competitiveness in AMMs, improving LP performance evaluations.

problem LP returns are affected by both market risk and competitive strategies.
method Introduces FLAIR metric to quantify LP competitiveness and assesses its impact on LP returns.
result FLAIR captures dynamic behavior of LPs and differentiates between active provisioning strategies.

Study on LP-Sasakian manifolds with generalized η-Ricci solitons.

problem Properties of LP-Sasakian manifolds with generalized η-Ricci solitons.
method Investigation of LP-Sasakian manifolds with generalized η-Ricci solitons associated to the general connection.
result Existence of generalized η-Ricci solitons on a 4-dimensional LP-Sasakian manifold.

In this paper, we give a new sharp generalization bound of lp-MKL which is a generalized framework of multiple kernel learning (MKL) and imposes lp-mixed-norm regularization instead of l1-mixed-norm regularization. We utilize localization techniques to obtain the sharp learning rate. The bound is characterized by the d…

2011-03-27abs ↗pdf ↗

The abstract discusses p-harmonic forms and their geometric properties, proving new theorems about Lp-cohomology.

problem The abstract tackles the geometric properties of p-harmonic forms and their role in Lp-cohomology.
method The approach involves using p-harmonic and p-coclosed forms to reprove vanishing theorems and provide injectivity theorems.
result The main finding is the reproof of vanishing theorems and the provision of injectivity theorems for Lp-cohomology.

Paper introduces a new multi-kernel algorithm for better gradient approximation.

problem Improving gradient approximation in high-dimensional problems.
method Develops a multi-kernel passive stochastic gradient algorithm with variance reduction.
result The multi-kernel algorithm performs better in high-dimensional problems.

Study on liquidity providers' performance in decentralized exchanges.

problem Unclear profitability of liquidity providers in decentralized exchanges.
method Reconstructing LP PnL dynamics from on-chain events, introducing a new metric.
result Only about one out of six LPs avoids losses, suggesting open questions about LP participation motives.

Classifies SL(n) covariant matrix-valued valuations on Lp-spaces.

problem Classifying SL(n) covariant matrix-valued valuations on Lp-spaces.
method Established a complete classification for continuous and SL(n) covariant matrix-valued valuations on Lp(Rn,|x|2dx), eliminating matrix symmetry assumption.
result Unique characterization of such valuations by the moment matrix in n>2, rotation matrix in 2D.

In this work we introduce a category of discrete Lagrange--Poincare systems LP_d and study some of its properties. In particular, we show that the discrete mechanical systems and the discrete mechanical systems obtained by the Lagrangian reduction of symmetric discrete mechanical systems are objects in LP_d. We introdu…

2015-11-20abs ↗pdf ↗

Active learning can't improve over passive in certain settings.

problem Active learning vs. passive learning in nonparametric settings.
method Analyzing margin conditions and their effects on active learning performance.
result Nuances in margin conditions determine whether active learning can outperform passive learning.

This paper aims to incorporate passive symmetries in machine learning for better generalization.

problem Machine learning's reliance on arbitrary choices leads to passive symmetries that can limit generalization.
method Translation among physics, mathematics, and machine learning to understand and implement passive symmetries.
result Respecting passive symmetries can improve machine learning's ability to generalize.

This paper investigates the market impact of passive orders.

problem Understanding the market impact of passive orders executed through limit orders.
method Developed a microstructure model linking liquidity dynamics and price moves, replacing the constant information content assumption with a function dependent on available volume.
result Derived useful approximations for market impact curves, leading to closed-form formulas.

New algorithm reduces online decision-making regret with efficient LP re-solving and parallel first-order method.

problem Worse regret guarantees and high computational cost of LP-based OLP algorithms.
method Combines LP-based and first-order OLP methods, re-solving LP subproblems periodically and using parallel first-order method.
result Achieves O(log(T/f)+f)\mathscr{O}(\log (T/f) + \sqrt{f}) regret, balancing computational efficiency and superior regret guarantee.

High-fee pools attract more liquidity but execute less volume; low-fee pools have more stable LPs.

problem Optimal liquidity supply and execution on decentralized exchanges with fixed gas costs.
method Analysis of Uniswap data to compare high- and low-fee pools.
result Fragmented liquidity leads to more LPs and competition, improving overall market efficiency.

Existence and uniqueness of the solution to the discrete Lp Minkowski problem for p\mathfrak{p}-capacity are proved when p1p \geq 1 and 1<p<n1<\mathfrak{p}<n. For general Lp Minkowski problem for p\mathfrak{p}-capacity, existence and uniqueness of the solution are given when p1p \geq 1 and 1<p21<\mathfrak{p}\le 2. These r…

2017-02-27abs ↗pdf ↗

We study the role of active and passive investors in an investment market with uncertainties. Active investors concentrate on a single or a few stocks with a given probability of determining the quality of them. Passive investors spread their investment uniformly, resembling buying the market index. In this toy market …

2001-04-18abs ↗pdf ↗

MAP inference for general energy functions remains a challenging problem. While most efforts are channeled towards improving the linear programming (LP) based relaxation, this work is motivated by the quadratic programming (QP) relaxation. We propose a novel MAP relaxation that penalizes the Kullback-Leibler divergence…

2012-06-18abs ↗pdf ↗

AI enhances refinery optimization by detecting data errors and improving decision-making.

problem Interpreting and applying LP solutions for refinery optimization is challenging due to simplifications and data errors.
method Transformed ECOD methodology, Anomaly Detection tools, and high-dimensional data analysis.
result Identifies data supply errors and reveals business opportunities in refinery scheduling and planning.

New formula identifies and quantifies costs for automated market makers.

problem Adverse selection costs faced by liquidity providers in automated market makers.
method Derives a Black-Scholes-like formula for AMMs and identifies loss-versus-rebalancing cost.
result Closed-form expressions for LVR applicable to all automated market makers.

New offline RL algorithm with optimal sample complexity using LP and error bounds.

problem Finding optimal policies from offline data with limited coverage and function approximation.
method Developed a new LP reformulation with error bounds and constraints for offline RL.
result Achieved optimal O(1/n)O(1/\sqrt{n}) sample complexity under various assumptions.

Modeling DEX liquidity with heterogeneous LPs and MEV bots.

problem Understanding and predicting the dynamics of decentralized cryptocurrency exchanges.
method Mean-field game approach to model liquidity providers' optimal strategies and interactions.
result Calibrated model produces consistent pool exchange rate dynamics and liquidity evolution.

This paper improves conformal prediction for robust interval estimation under distribution shifts.

problem Robustness of conformal prediction under distribution shifts.
method Modeling distribution shifts using Levy-Prokhorov (LP) ambiguity sets, which capture both local and global perturbations.
result Constructs robust conformal prediction intervals that remain valid under distribution shifts.

LP-FT improves personalized model training in FL by balancing generalization and personalization.

problem Federated Learning struggles with balancing global generalization and local personalization due to non-identical data distributions.
method Adapting Linear Probing followed by full Fine-Tuning (LP-FT) to the FL setting.
result LP-FT outperforms standard fine-tuning in balancing personalization and generalization across various datasets and PFT variants.

Paper optimizes liquidity provision in decentralized finance markets.

problem Strategic LPs face predictable losses and concentration risk in CL pools.
method Derive optimal liquidity provision strategy based on fees, PL, and concentration risk.
result Optimal strategy increases fee revenue and profit from marginal rate changes.